Wednesday, September 23, 2015

AAT is an anti-inflammatory / immunomodulatory drug, which the body makes naturally, and which is already FDA approved for people who have a rare condition where they don't make enough of it on their own. Using AAT to treat type-1 diabetes is based on the idea that one of AAT's effects (lowering inflammation, immune modulation, or wound healing) can cure/prevent/treat the disease.

This study was open label, with no control group. A total of 24 people were divided into three groups and each group got a different dose [d1]. Primary end points were safety related, but effectiveness was measured in secondary end points. The study lasted 37 weeks. The patients got a total of 18 doses of AAT, spread out over the first 28 weeks of the trial.

The results were:

No serious adverse events occurred, and non-serious adverse events were not dose dependant.

Average hemoglobin A1c decreased from 8.4% to 7.1% [my rounding].

C-peptide levels dropped during the study, but the researchers felt that they dropped less than seen in untreated people from other studies. At the end of the study, 18 subjects (75%) had a peak C-peptide ≥0.2 pmol/mL.

At the end of the study 1/3 of the subjects met the definition of "possible responder" meaning their C-peptide numbers had gone down 7.5% or less.

Opinions of Results

First, no serious adverse events is a good safety result, and having non-serious adverse events be non-dose dependent is also a good safety result. If there were safety issues, they would likely get stronger as the dose gets higher, since that did not happen, it is likely that these adverse events were not related to the treatment. So it looks like it passed the safety part of the trial.

Because this study was done on youth between 10 and 18 years old, showing a good safety profile is particularly important. It is likely to open up future trials to youth. Recruiting youth speeds the clinical trial process (especially in the honeymoon phase) because type-1 is so often first diagnosed in children. The safety profile might also lower barriers to "off label" use of this drug [d2].

Now an optimist would say "phase-I tests safety and safety is OK, so trial is a success". However, they did measure effectiveness also, and so I do think it is important to look at the effectiveness numbers that we have. I have noticed that if the phase-I is not effective, it makes it less likely that the phase-II will be. So with that in mind:

The most important thing to remember is that this study did not have a control group, and that makes interpreting the results difficult. The A1c group, the C-peptide group, and the "responder" group all have the same fundamental difficulty: we know what happened to the treated people, but there is no untreated group to directly compare them to. Therefore the researchers compare these people with untreated people from other studies; and I'm doing the same.

I think that the drop in A1c levels was meaningless. This was a honeymoon trial; people were recruited within 6 months of diagnosis. That first A1c number covers either the early months of type-1 diabetes self treatment or the weeks just before diagnosis (or some of each). These are both times of high A1c numbers. Conversely, the second A1c number covers a time when the patient has between 6 and 12 months of experience with type-1, and is therefore better at treating their type-1. So of course the A1c numbers are better.

The researchers compare these A1c numbers to average A1c numbers in adults, and note that the first is above average while the second is below. However, for the reasons described above, I don't think this is a case where comparing to average is an appropriate thing to do.

For the C-peptide data, I think the data is hard to interpret, but disappointing. The researchers summarized their findings this way:

subjects treated with AAT showed less of a decline in C-peptide levels as compared with historical controls. However, in the absence of a randomized control group, these findings should not be interpreted as showing a beneficial effect on beta cell preservation
and glycemic control.

For me "less of a decline" is the very smallest sign of success a researcher can talk about. I'd put these results below results from TOL-3021 and Alefacept (both which held C-peptides constant), and maybe even Teplizumab (which held C-peptides constant in some people).

Each person has to decide for themselves which results excite them, and which don't. For my part, in honeymoon trials, results where the C-peptide numbers go up (after a year) excite me. Results where they stay constant are unexciting. And, results where they go down are disappointing. Here the average went down.

People in this study will be offered a chance to participate in a long term (3 year) follow up study. Those who still generate C-peptides [d3] will be kept on their current dose of AAT. Those who don't (or who don't want to continue, will not get AAT, but will be followed as a comparison group.

Overall Status of AAT As A Cure For Type-1

AAT is unusual, in that there are two different types of information on it. There are results of previous clinical trials. But there are also anecdotal reports from the popular press. The anecdotal reports are far more positive. Unfortunately, these phase-I reports are clearly in line with the previous clinical trial results. They are lackluster and will not lead to a cure without a large improvement in effectiveness.

The good news is that there are two phase-II clinical trials of AAT already underway, so there is nothing to do but wait. Especially since one of those phase-II trials is being done by the same company as did this trial: they have incorporated what was learned from the older trial into the design of the newer trial. If there are good results from the phase-II trials, then AAT is in good shape. Mediocre results in phase-I mean nothing if the phase-II results are good. If those results are as good as the anecdotal results, then AAT is in great shape. But if those phase-II results are similar to these phase-I results, then that would be bad news for AAT.

Opinionated Discussion of Footnote 30

Because this study did not have a control group of it's own, the researchers used control group data from other studies. In particular, some control group data from the phase-II trial of DiaPep 277, and this reference was provided in footnote 30. In my opinion, using this data raises a red flag. One of DiaPep's phase-III trials was canceled because of serious scientific misconduct [d4]. The article reporting the results of the other phase-III trial was retracted because the same misconduct was found in that study as well. To my knowledge, no misconduct has been found in the phase-II trial, but none was particularly looked for, either. And there are authors in common between the retracted phase-III paper, and the cited phase-II paper [d5]. Finally, the manipulation that was done in the phase-III paper changed both the treated group and the control group [d6]. So if that same manipulation was done to the phase-II trial, (that is a big "if" of course) then it would effect the exact data that these AAT researchers are using.

For all these reasons, I think using data from the DiaPep 277 phase-II study is a mistake. The AAT researchers were using control group data. Lots of studies have control groups. Why use potentially tainted data, when untainted data is available?

Thanks

I want to specifically thank the author of this paper who sent me a copy of the full paper, so I could comment on all of the paper, and not just the abstract.

More Discussion

[d1] The researchers listed this trial as "Phase-I/II". Generally I consider phase-I to be less than 20 people, and phase-II to be larger than that, but I also expect a Phase-II to have a control group, which this did not. So based on the whole trial, I consider this a phase-I trial.

[d2] In the USA once a drug or device is approved, a doctor can prescribe it in situations different than it was originally approved for. As an example, a doctor may prescribe it for a different disease, at a different dose, or for a different type of person than it has been approved for. In the world of type-1 treatments, drugs or devices that have been approved for use on adults are often prescribed for children. This is a classic "off label" use. Off label use is based on the professional opinion of a doctor, and consent of the patient. Therefore safety data (such as from this study) can make doctors more willing to prescribe "off label", and patients more interested in trying it.

[d3] Specifically, patients who have C-peptide levels of ≥ 0.2nmol/L will be able to continue their AAT regimen. Note also that I refer to the other group as a "comparison" group and not a "control" group. These two groups start off different, so I don't consider one to be a good control for the other.

[d4] Hyperion used the term "serious misconduct" in describing the situation, and Globe News used the term "fraud".

[d5] I want to stress that there were authors who only worked on the phase-II paper, and there were authors who only worked on the phase-III paper. And, there were authors who worked on both papers. To my knowledge, there has never been a public naming of who was involved in the misconduct, so there is no way to know if one of the authors was involved or if it was someone else in the organization, or even how many people were involved.

Joshua Levy http://cureresearch4type1diabetes.blogspot.com publicjoshualevy at gmail dot com All the views expressed here are those of Joshua Levy, and nothing here is official JDRF or JDCA news, views, policies or opinions. My daughter has type-1 diabetes and participates in clinical trials, which might be discussed here. My blog contains a more complete non-conflict of interest statement. Thanks to everyone who helps with the blog.

Tuesday, September 1, 2015

This blog posting applies to all clinical trials, not just those for type-1 diabetes.

I try to avoid using technical jargon when I describe clinical trials. I think one of the values of this blog is that I turn technical jargon in to plain English. (I sometimes joke about providing "researcher to patient simultaneous translation", but it's not really a joke. It's important.) However, one technical term that I do use is "adverse event". "Adverse event" generally means "bad side effect". Serious adverse event generally means "really bad side effect". But the truth is more complex than this simplified version, and so I thought I would make a post describing exactly what "adverse event" and "serious adverse event" means, because these terms are defined by the US FDA, and their meaning is the same no matter which clinical trial I'm discussing.

An "adverse event" is any bad effect seen in the study. The FDA uses the term "undesirable experience". It does not have to be caused by the treatment!

A "serious adverse event" is an adverse event that causes death, hospitalization, persistent or significant disability, or a birth defect. Or one which requires immediate medical attention to prevent one of these outcomes.

For example, a mild allergic reaction would usually be considered an "adverse event", but if the patient had trouble breathing, that would be a "serious adverse event".

The First Complexity: How Bad Is Serious?

No matter how many rules the FDA makes, and how many documents it publishes, there will always be room for researchers to interpret a specific events as serious or not. Therefore, there will always be controversies about it.

For example, in one Chronic Fatigue Study there was controversy because several adverse events required patients to go to a clinic (but not a hospital). Now hospitalization clearly means serious, but the company producing the drug felt that going to a clinic was not a sign of a serious adverse event. When the FDA reviewed the study, they disagreed, and the the larger number of serious adverse events the FDA counted were part of the reason the drug was not approved.

The Second Complexity: Treatment Related Or Not?

In general, researchers are required to track all adverse events, no matter what their cause. The FDA terminology is "associated with" not "caused by". After all, these are experimental treatments and some of the bad side effects might be unexpected. I've seen a trial for an immune system drug, which listed one serious adverse event: a broken arm. Now, I don't think that broken arm had anything to do with the immune treatment being tested. But it is still a serious adverse event, and must be reported.
A more complex situation is adverse events associated with the disease being treated. For example, if you are testing a drug for depression, and someone in the study commits suicide, that is clearly a serious adverse event, but is it treatment related? How would anyone ever know?

This whole area is usually resolved by comparing adverse event rates between the control group and the treated group. If there are statistically significantly more adverse events in the treated group as compared to the control group, that is the important result. Arguing that some of these adverse events are not "treatment related" much less important. More adverse events is bad, no matter if the researchers think they are not related to treatment. But what about those phase-I trials that don't have control groups? For those trials, arguing about "treatment related" can be important.

The Third Complexity: Who Decides?

Someone goes through every event and decides if it is serious or not. The same is true for "treatment related" if that is reported separately. Obviously, this is a human activity and the results will be imperfect, but the exact procedure used can minimize (or maximize) risk of bias. The two things to look for are blinding and reviewers.

The review can be done "blind" or not "blind". The reviewer looks at the event, and maybe some data about the person who had the event, but does not know if the person is in the control group or the treated group (or what dose the person got, if multiple doses were tested). But if the reviewer knows that the event occurred in the control group or the treated group, the risk of bias is more pronounced. If the study doesn't have a control group, then this review will never be blind.

The reviewing is usually done by the same researchers running the trial. However, it can be done by a different group of doctors, recruited especially for that purpose. Having a different group lowers the risk of bias, and this is done for some particularly controversial or emotional trials.

Some Discussion and Opinions

Overall, I think we are lucky in the world of type-1 diabetes research, in that the reporting of adverse events is generally not complex or controversial. Type-1 diabetics are generally pretty healthy, and also the bad complications of type-1 diabetes are generally well understood. Therefore, there is consensus as to the types of adverse events that are likely related to treatment, and those that are not.

Especially in larger clinical trials, serious adverse events will happen. So the important thing to look at is: Were there more serious adverse events in the treated group than in the control group? Also, if multiple different doses were given to different groups of people, do the higher dosed groups see more serious adverse events, or are they randomly spread throughout all the dosing groups?

Since all adverse events must be reported, it is important to consider the impact of different adverse events as compared to the disease being treated. For example, rashes or mild fevers are common adverse events (not serious ones). Compared to curing type-1 diabetes, these might be well worth it. On the other hand, in a drug which merely treats type-1, the very same adverse event might cause you to use a different drug.

Because the long term outcomes of type-1 diabetes is relatively well known, it's easy for patients to "trade off" the adverse events seen in testing a cure, to the long term complications of having type-1 diabetes.

One problem in the whole approval process is the issue of very rare side effects, especially those which happen rarely in healthy, untreated people. Take the following situation, you treat 300 basically healthy, basically young, people with a drug. One of them has a stroke. That's a serious side effect. But it is something that happens -- although very rarely -- in young people who are not taking the drug. With 300 people you may not have the statistical power to know if it is a statistically significant event. Are you going to delay availability and require a larger (and very expensive) study just to eliminate the statistical chance that the drug causes stroke? Or maybe approve the drug, but require a strong (ie. "black box") warning about stroke? Or just decide that it was random bad luck, and approve the drug?
(The situation is much worse with diseases like type-2 diabetes. Was that stroke caused by type-2 diabetes, or the drug given to treat the type-2 diabetes?)

In a sense, the FDA cannot win in these cases, because no matter which outcome they choose, some people will want the other one. So if the drug is delayed, some patients (and the company involved) will scream loudly about delaying needed treatments and creating unnecessary hurdles to drug approval. On the other hand, if the drug is approved, another group of patients (and consumer advocates) will yell about approving dangerous drugs so big pharma can profit. If the drug is given to 10,000 and one of them has a stroke (by chance? or because of the drug?) then recriminations will be deafening.

Joshua Levy http://cureresearch4type1diabetes.blogspot.com publicjoshualevy at gmail dot com All the views expressed here are those of Joshua Levy, and nothing here is official JDRF or JDCA news, views, policies or opinions. My daughter has type-1 diabetes and participates in clinical trials, which might be discussed here. My blog contains a more complete non-conflict of interest statement. Thanks to everyone who helps with the blog.

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This blog discusses cures and preventatives for type-1 diabetes that are either in human trials or just about to start. Treatments for diabetes are not generally discussed here, unless they can turn into a cure or a preventative. My definition of a cure is this:1. Blood sugar control without testing and with doctor's visits 4 times a year, or less. Any cure must result in an average lifespan close to normal.2. Does not require a lifetime of immunsuppressive drugs, so it is not trading one treatment for another. (but a couple of operations, or a short course of drugs is OK)Obviously, this is my personal definition of a cure; yours may differ.Because a cure for type-1 diabetes is likely to involve a combination of several different drugs or treatments, I try to follow research into anything which may be an important part of the cure.

My Non-Conflict of Interest Statement

I don't work for a company involved in medical research; I never have.

I don't get paid in any way by any company doing medical research; I never have. And that includes free samples, free travel, or free anything. I do sometimes participate in market research studies or focus groups, and they sometimes pay.

None of the hours that I have put into my blog, or the posts that I make to any web site, has ever been paid for. (Except for some very nice and heart felt thank-you emails, and those are worth more than money.)

My daughter has type-1 diabetes and participates in clinical trials. I sometimes report on trials that she participates in, but I do not reveal her participation because I consider her medical history to be private.

I sometimes "beta test" new software or devices involved in type-1 diabetes. When I'm blogging about something where I have been given special access, I say so.

In the past I have volunteered with JDRF, The NIIB Project, and I currently am a fellow with JDCA. JDRF and NIIB Project was completely unpaid. JDCA has given me equipment that I use to help my blogging.

Over the years my daughter has used several types of insulin, several types of meters, and pumps made by different manufacturers. I don't always mention if I'm blogging about a company who's products she uses now or in the past (there are so many).